Triple
T17577757
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Region A |
E428115
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Carlswald |
—
|
NE NERFINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Carlswald | Statement: [Region A, contains, Carlswald]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Carlswald Context triple: [Region A, contains, Carlswald]
-
A.
Carlswald
chosen
Carlswald is a residential and commercial suburb located in the Midrand area between Johannesburg and Pretoria in South Africa.
-
B.
Callisburg
Callisburg is a small rural city located in Cooke County in northern Texas, United States.
-
C.
Arzdorf
Arzdorf is a village and district of the municipality of Wachtberg in the Rhein-Sieg-Kreis region of North Rhine-Westphalia, Germany.
-
D.
Gaildorf
Gaildorf is a small town in the German state of Baden-Württemberg, situated in the Kocher River valley and known for its historic center and surrounding rural landscape.
-
E.
Lonnerstadt
Lonnerstadt is a small municipality in the Erlangen-Höchstadt district of Bavaria, Germany, known for its rural character and Franconian cultural heritage.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d889e0385081908a04b66f4dd4bd0d |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e463cb40088190b726f2c026358cf2 |
completed | April 19, 2026, 5:10 a.m. |
Created at: April 10, 2026, 5:50 a.m.